Project Summary The cerebellum is an evolutionarily conserved brain structure known to contribute to motor control. A leading hypothesis of cerebellar function is that it generates an internal model to predict upcoming body kinematics allowing the cerebellum to provide feedforward motor control to make movements smooth and accurate. Current theories propose that the sole outputs of the cerebellar cortex ?Purkinje cells (PC)? predict future movement kinematics in simple spike (SS) firing rates. These SSs are driven by mossy fiber inputs that indirectly contact PCs via parallel fibers. It is thought that complex spikes (CSs), driven by inferior olivary climbing fibers synapsing onto PCs, drive plasticity of parallel fibers allowing PCs to learn to respond to incoming mossy fiber information. In this way, CSs adjust the SS rate to model upcoming movements. However, how PCs incorporate their two extracerebellar inputs? mossy fibers and climbing fibers? to produce SS predictive encoding in limb movements, like reaching, is unclear. This study will relate the electrophysiological signals of these two inputs? SSs and CSs? during a mouse reaching task. By using multilinear regression models and closed-loop optogenetics, I will test how CS-driven changes in SS encoding lead to accurate predictions of limb position by PCs. I hypothesize that SS kinematic tuning is shaped by ?encoding error?-triggered CSs. This hypothesis would be distinct from current ?target error?-based theories of CS firing and would have the ability to explain how PCs shape movements across an entire reach, not just at the endpoint.